EdgeInfinite introduces a memory-efficient transformer architecture that enables processing of unbounded text sequences on edge devices without the typical memory constraints.

• Adaptive KV Cache Management: Dynamically manages attention memory without irreversible token eviction
• Reduced Memory Footprint: Minimizes RAM requirements while maintaining performance
• Long-Output Capability: Supports tasks requiring extended generation without degradation
• Infrastructure Compatible: Integrates with existing transformer frameworks without architectural overhauls

This innovation is significant for engineering as it brings powerful LLM capabilities to resource-constrained environments, enabling AI applications on smartphones, IoT devices, and other edge computing scenarios without requiring cloud connectivity.

EdgeInfinite: A Memory-Efficient Infinite-Context Transformer for Edge Devices